Image retrieval is a problem in the field of information retrieval. An algorithm was developed for image retrieval based on scale invariant feature transform (SIFT), K-Means and latent dirichlet allocation (LDA). This algorithm was mainly divided into two stages. The preparations obtained the classified image library, the probability distribution of parameters table and the base vocabulary library; the retrieval classified the test image based on the preparations, and looked up the most similar image. Compared with the traditional methods based on text or content, the algorithm classifies automatically all the images in the library before the retrieval, which can replace the process of manual label. Meanwhile, the algorithm is based on image feature fully, which will not introduce artificial disturbances. Experimental results show that the algorithm can classify accurately the test image as the corresponding category, which can increase efficiency of the retrieval.

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